AI for Marketers: Initial Insights

I have spoken to about 150 VPs of Marketing and CMOs from around the country, and have gotten more feedback in writing with the LinkedIn messenger. The questions I’m asking are very general and sometimes hard to answer concisely, but it gives us a good feel for how versed marketers are with what Artificial Intelligence (AI) means, exactly, and what the differences are between AI and Machine Learning and Deep Learning.

The questions are:

1. Are you attempting to use AI in any way to attempt to solve a marketing problem?
2. Do you find it difficult to measure ROI and if so how do you think AI could help?

My first impression is that marketers are very up to speed on what these terms mean then I would have originally guessed. Most marketers (from all age groups I might add) state that we don’t really have “true” Artificial Intelligence. And that is correct! We are still a few years away from true AI (actually defining true AI is a topic for another post). Machine Learning and Deep Learning are the techniques used by organizations to automate their processes, improve transparency, and apply ‘agile marketing’ techniques to improve defined metrics.

Deep learning and machine learning are used in conjunction to achieve the marketers desired results. There are a ton of examples of how these techniques can work together to improve specific metrics…I’ll give an example by telling a small story :).

Let’s say we have a customer at a restaurant.

Before deep learning and machine learning:

My food is cold! Copyright Rewards Network, all rights reserved.

In the old days, restaurants would tell us to fill out a survey (remember those?) asking us to fill out a few customer satisfaction questions. These questions would lead to insights, which would trigger an action from management to improve the quality of certain deliverables. One of the questions is ‘was the food served to you at the right temperature?”. It would take weeks or months for management to act on these results if anything needed correcting.

With deep learning and machine learning:

The user sends out a Tweet or an Instagram post stating that the food is cold. Restaurants bots pick up on that information with deep learning natural language processing (NLP). The restaurant then enriches contact information and by using LinkedIn determines that this person is actually a food critic and is a big influencer in the Foodie community. A machine learning model exists that puts a lot of weight on Foodie influencers so it then triggers an action and sends an alert to the manager on site and records the event for future follow up. The manager, without the customer, even knowing it, approaches the customer and offers a solution. Not only that, but the manager can offer a solution with context!

I bet a restaurant that implements the latter techniques will be more successful than the former, all else being equal.

We have many more insights that we want to share with you and are really looking forward to sharing our future posts!

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